Reducing case ascertainment costs in U.S. population studies of Alzheimer's disease, dementia, and cognitive impairment-Part 2

Abstract

Dementia of the Alzheimer's type (DAT) is a major public health threat in developed countries where longevity has been extended to the eighth decade of life. Estimates of prevalence and incidence of DAT vary with what is measured, be it change from a baseline cognitive state or a clinical diagnostic endpoint, such as Alzheimer's disease. Judgment of what is psychometrically "normal" at the age of 80 years implicitly condones a decline from what is normal at the age of 30. However, because cognitive aging is very heterogeneous, it is reasonable to ask "Is 'normal for age' good enough to screen for DAT or its earlier precursors of cognitive impairment?" Cost containment and accessibility of ascertainment methods are enhanced by well-validated and reliable methods such as screening for cognitive impairment by telephone interviews. However, focused assessment of episodic memory, the key symptom associated with DAT, might be more effective at distinguishing normal from abnormal cognitive aging trajectories. Alternatively, the futuristic "Smart Home," outfitted with unobtrusive sensors and data storage devices, permits the moment-to-moment recording of activities so that changes that constitute risk for DAT can be identified before the emergence of symptoms.

Fig. 1

Home layout showing a typical array of sensors unobtrusively installed in existing homes to monitor activity and function on a continuous basis. Many other technologies or devices can also be added to this sensor net such as bed activity mats, telephone monitors, or physiological measuring devices (scales, oximeters, glucometers, etc.) depending on need. See key for explanation of symbols. For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.

Fig. 2

Daily walking speed measurements (cm/s) for an individual derived from an in-home sensor line operating over a period of 16 months showing the natural variability in this metric associated with cognitive decline . The automated measure provides a more comprehensive view of walking compared to current single point speed measures represented in the figure as the two red data points obtained with a stopwatch at widely spaced intervals. Uniquely, this methodology allows for the calculation of trends over time (red line) as well as defining naturally occurring populations of fast or slow walks (dashed lines) for an individual. For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.

Fig. 3

The bars represent the ability of two groups of elderly individuals to adhere to a twice daily medication-taking regimen assessed using a medication tracking device (inset) that automatically records the time of day when a pill compartment is opened. Those scoring greater than the upper limit of the 95% confidence interval on the Alzheimer’s Disease Assessment Scale cognitive subscale (higher scores represent poorer performance) were significantly less able to adhere to the medication regimen. These results suggest the ability to detect subtle deficits in cognitive function using performance on a daily task that is unobtrusively monitored in real time. Data are from Hayes et al [64]. For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.

Fig. 4

The graph represents a translation of data from normative tables of the subtests of the Wechsler Memory Scale—third edition [38]. To generate the data points, the raw score equivalent of a scaled score of 10 was plotted for each subtest for each age group included in the normative tables. If, for a particular test, the raw score was a range rather than a single value, the average of the scores was computed to generate the graph. The trajectory is unequivocally downward over the age groups from youngest to oldest. However, each subtest has its own aging trajectory, with some showing sharper decline than others over the same period.